Photoresponsive Nanogels Based on Photocontrollable Cross-Links
Bibliographic record
Abstract
We present a new and general strategy for preparing photoresponsive nanogels. It is based on using light to reversibly change the cross-linking density of nanogel particles to control their swelling degree in aqueous solution. This control mechanism allows for gradual volume change of nanogel particles by light. For proof of concept, diblock copolymers composed of poly(ethylene oxide) and poly[2-(2-methoxyethoxy)ethyl methacrylate- co -4-methyl-[7-(methacryloyl)oxyethyloxy]coumarin] (PEO- b -P(MEOMA- co -CMA)) were synthesized; nanogels could easily be prepared by first photo-cross-linking the micellar aggregates at T > LCST of the P(MEOMA- co -CMA) block through dimerization of coumarin side groups upon absorption of λ > 310 nm UV light and then cooling the solution to T < LCST to obtain cross-linked water-soluble polymer nanoparticles. Under λ < 260 nm UV light, the reverse photocleavage of cyclobutane rings could be used to reduce the cross-linking density, leading to the swelling of nanogel particles with a volume increase by about 90%. The reversibility of the photoinduced volume change, the effects of the molecular weight of P(MEOMA- co -CMA) block and the content of coumarin groups on the photoresponsive behavior, and the use of nanogel particles for photocontrolled release were investigated.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".